run.cin.cyto {CINdex} | R Documentation

## Calculate cytoband CIN

### Description

`run.cyto.chr` calculates cytoband level CIN for the following default thresholds (with and without normalization): (a) gain threshold 2.5 and loss threshold 1.5 (b) gain threshold 2.25 and loss threshold 1.75 (c) gain threshold 2.10 and loss threshold 1.90. For each of these threshold settings, this function will calculate CIN for gains, losses, and a combination of gains and losses (referred to as 'sum' or 'overall' CIN). This will allow user to examine and select the best setting of gain and loss threshold for their data. More details and tutorial are given in the accompanying vignette.

### Usage

    run.cin.cyto(grl.seg, cnvgr = NULL, snpgr = NULL, genome.ucsc,
      out.folder.name = "output_cyto_cin", thr.gain = c(2.5, 2.25, 2.1),
      thr.loss = c(1.5, 1.75, 1.9), V.def = 2:3, V.mode = c("sum", "amp",
      "del"), chr.num = 22)

### Arguments

`grl.seg` | The result of any segmentation algorithm such as CBS,FMR. Should be a GRangesList
`cnvgr` | Probe annotation info for the copy number probes - GRanges object
`snpgr` | Probe annotation info for the SNP probes - GRanges object
`genome.ucsc` | A Reference genome
`out.folder.name` | Name of output folder, where the CIN objects for each setting will be created
`thr.gain` | A numeric list that contains values set as threshold gain
`thr.loss` | A numeric list that contains values set as threshold loss
`V.def` | An integer vector that has 2 different CIN definitions - normalized (value=2) and un-normalized (value=3)
`V.mode` | A vector that has 3 options: 'sum', 'amp' and 'del'
`chr.num` | Number of chromosomes in input. Typically 22.

### Value

Creates a dataMatrix and cytobands.cin R objects for each setting that contains CIN values

### See Also

Accompanying vignette for complete end-to-end tutorial

### Examples

    #### For this example, we run cytoband CIN calculation for one setting on chromosome 1 only
    data("grl.data") #need segment level data

    #getting genome reference file
    data("hg18.ucsctrack")
    hg18.ucsctrack.chr <- subset(hg18.ucsctrack, seqnames(hg18.ucsctrack) %in% "chr22")

    #get probe annotation information
    data("cnvgr.18.auto")

    #Call function to run cytoband CIN
    run.cin.cyto(grl.seg = grl.data, cnvgr=cnvgr.18.auto, snpgr=NULL,
    genome.ucsc = hg18.ucsctrack.chr, thr.gain = 2.25,thr.loss = 1.75,
    V.def = 3, V.mode="sum",chr.num = 22)

    #Run cytoband level CIN calculation for all thresholds. This is how command should be run:
    ## Not run:
    run.cin.cyto(grl.seg = grl.data, cnvgr=cnvgr.18.auto, snpgr=snpgr.18.auto,
    genome.ucsc = hg18.ucsctrack)

    ## End(Not run)
    # A number of RData objects will be created in 'output_cyto' folder.

[Package CINdex version 1.8.0 Index]